OpenRaiser/Intern-Atlas huggingface dataset:
On cyclic DNA codes over the rings Z_{4}+wZ_{4} and Z_{4}+wZ_{4}+vZ_{4}+wvZ_{4}
Venue: arXiv cs.IT 2016
Year: 2016

The structures of cyclic DNA codes of odd length over the finite rings R=Z_{4}+wZ_{4}, w^{2}=2 and S=Z_{4}+wZ_{4}+vZ_{4}+wvZ_{4},w^{2}=2,v^{2}=v,wv=vw are studied. The links between the elements of the rings R, S and 16 and 256 codons are established, respectively. Cyclic codes of odd length over the finite ring R satisfies reverse complement constraint and cyclic codes of odd length over the finite ring S satisfy reverse constraint and reverse complement constraint are studied. Binary images of the cyclic DNA codes over the finite rings R and S are determined. Moreover, a family of DNA skew cyclic codes over R is constructed, its property of being reverse complement is studied.
Implementation of linear detection techniques to overcome channel effects in MIMO
Venue: arXiv cs.IT 2016
Year: 2016

Spatial diversity technique enables improvement in quality and reliability of wireless link. Antenna diversity along with understanding effects of channel on transmitted signal and methods to overcome the channel impairment plays an important role in wireless communication where sharing of channel occurs between users. In this paper single input single output system (SISO) is compared with multiple input multiple output system (MIMO) in terms of bit error rate performance. Bit error rate performance is also evaluated for MIMO with least squares (LS) and Minimum mean square error (MMSE) linear detection. Further analysis and simulation is done to understand the effect of channel imperfections on BER.
Asymptotics of Insensitive Load Balancing and Blocking Phases
Venue: arXiv cs.PF 2016
Year: 2016

We address the problem of giving robust performance bounds based on the study of the asymptotic behavior of the insensitive load balancing schemes when the number of servers and the load scales jointly. These schemes have the desirable property that the stationary distribution of the resulting stochastic network depends on the distribution of job sizes only through its mean. It was shown that they give good estimates of performance indicators for systems with finite buffers, generalizing henceforth Erlang's formula whereas optimal policies are already theoretically and computationally out of reach for networks of moderate size. We study a single class of traffic acting on a symmetric set of processor sharing queues with finite buffers and we consider the case where the load scales with the number of servers. We characterize central limit theorems and large deviations, the response of symmetric systems under those schemes at different scales and show that three amplitudes of deviations can be identified. A central limit scaling takes place for a sub-critical load; for $ρ=1$, the number of free servers scales like $n^{ {θ\over θ+1}}$ ($θ$ being the buffer depth and $n$ being the number of servers) and is of order 1 for super-critical loads. This further implies the existence of different phases for the blocking probability, Before a (refined) critical load $ρ_c(n)=1-a n^{- {θ\over θ+1}}$, the blocking is exponentially small and becomes of order $ n^{- {θ\over θ+1}}$ at $ρ_c(n)$. This generalizes the well-known Quality and Efficiency Driven (QED) regime or Halfin-Whitt regime for a one-dimensional queue, and leads to a generalized staffing rule for a given target blocking probability.
Eco-Strategy: Towards a New Generation Managerial Model Based on Green IT and CSR
Venue: arXiv cs.CY 2016
Year: 2016

The sustainable development strategy in the management of information and communication technology (ICT) is an advanced research sector which provides a theoretical framework for integrating social and environmental responsibilities of business in the development and implementation of the management strategy. This article offers an original management model that integrates the Corporate Social Responsibility (CSR) approach and Green IT, which enables decision makers, governance and strategic alignment of ICT, business and sustainability. The model offers a new vision of decision making through economic opportunities and increasing pressure from stakeholders. This paper reveals the strategic relevance of the model, on the basis of a literature review, and provides guidelines for sustainable business development of effective management systems, and improvement of the economic, social and environmental performance of companies. The proposed framework provides a new generation managerial approach to ICT management strategy that we call "Eco-Strategy".
Avoiding Wireheading with Value Reinforcement Learning
Venue: arXiv cs.AI 2016
Year: 2016

How can we design good goals for arbitrarily intelligent agents? Reinforcement learning (RL) is a natural approach. Unfortunately, RL does not work well for generally intelligent agents, as RL agents are incentivised to shortcut the reward sensor for maximum reward -- the so-called wireheading problem. In this paper we suggest an alternative to RL called value reinforcement learning (VRL). In VRL, agents use the reward signal to learn a utility function. The VRL setup allows us to remove the incentive to wirehead by placing a constraint on the agent's actions. The constraint is defined in terms of the agent's belief distributions, and does not require an explicit specification of which actions constitute wireheading.
Dead Letters to Alice - Reachability of E-Mail Addresses in the PGP Web of Trust
Venue: arXiv cs.CR 2016
Year: 2016

Over the last 25 years four million e-mail addresses have accumulated in the PGP web of trust. In a study each of them was tested for vitality with the result of 40% being unreachable. Of the mailboxes proven to be reachable, 46.77% turn out to be operated by one of three organizations. In this article, the authors share their results and challenges during the study.
Towards a Technique for Extracting Microservices from Monolithic Enterprise Systems
Venue: arXiv cs.SE 2016
Year: 2016

The idea behind microservices architecture is to develop a single large, complex application as a suite of small, cohesive, independent services. On the other way, monolithic systems get larger over the time, deviating from the intended architecture, and becoming risky and expensive to evolve. This paper describes a technique to identify and define microservices on monolithic enterprise systems. As the major contribution, our evaluation shows that our approach was able to identify relevant candidates to become microservices on a 750 KLOC banking system.
On "Exponential Lower Bounds for Polytopes in Combinatorial Optimization" by Fiorini et al. (2015): A Refutation For Models With Disjoint Sets of Descriptive Variables
Venue: arXiv cs.CC 2016
Year: 2016

We provide a numerical refutation of the developments of Fiorini et al. (2015)* for models with disjoint sets of descriptive variables. We also provide an insight into the meaning of the existence of a one-to-one linear map between solutions of such models. *: Fiorini, S., S. Massar, S. Pokutta, H.R. Tiwary, and R. de Wolf (2015). Exponential Lower Bounds for Polytopes in Combinatorial Optimization. Journal of the ACM 62:2, Article No. 17.
Unsupervised Semantic Action Discovery from Video Collections
Venue: arXiv cs.CV 2016
Year: 2016

Human communication takes many forms, including speech, text and instructional videos. It typically has an underlying structure, with a starting point, ending, and certain objective steps between them. In this paper, we consider instructional videos where there are tens of millions of them on the Internet. We propose a method for parsing a video into such semantic steps in an unsupervised way. Our method is capable of providing a semantic "storyline" of the video composed of its objective steps. We accomplish this using both visual and language cues in a joint generative model. Our method can also provide a textual description for each of the identified semantic steps and video segments. We evaluate our method on a large number of complex YouTube videos and show that our method discovers semantically correct instructions for a variety of tasks.
Talk More Listen Less: Energy-Efficient Neighbor Discovery in Wireless Sensor Networks
Venue: arXiv cs.NI 2016
Year: 2016

Neighbor discovery is a fundamental service for initialization and managing network dynamics in wireless sensor networks and mobile sensing applications. In this paper, we present a novel design principle named Talk More Listen Less (TMLL) to reduce idle-listening in neighbor discovery protocols by learning the fact that more beacons lead to fewer wakeups. We propose an extended neighbor discovery model for analyzing wakeup schedules in which beacons are not necessarily placed in the wakeup slots. Furthermore, we are the first to consider channel occupancy rate in discovery protocols by introducing a new metric to trade off among duty-cycle, latency and channel occupancy rate. Guided by the TMLL principle, we have designed Nihao, a family of energy-efficient asynchronous neighbor discovery protocols for symmetric and asymmetric cases. We compared Nihao with existing state of the art protocols via analysis and real-world testbed experiments. The result shows that Nihao significantly outperforms the others both in theory and practice.
Effective Road Model for Congestion Control in VANETs
Venue: arXiv cs.NI 2016
Year: 2016

Congestion on the roads is a key problem to deal with, which wastes valuable time.. Due to high mobility rate and relative speed link failure occur very often. VANET is used to tackle the problem of congestion, and make decisions well in advance to avoid traffic congestion. In this paper we proposed a solution to detect and control the traffic congestion by using of both (V2V) and (V2I), as a result the drivers become aware of the location of congestion as well as way to avoid getting stuck in congestion. The congestion is detected by analyzing the data obtained by vehicular communication and road side units to avoid the traffic. Our proposition system is competent of detecting and controlling traffic congestion in real-time. V2V and V2I communication network is used to receive and send the messages. We simulate the result by using Congestion Detection and Control Algorithm (CDCA), and show that this is one effective way to control congestion. The Proposed methodology ensures reliable and timely delivery of messages to know about congestion and avoid it. KEYWORD: CDCA ALGORITHM, INTELLIGENT TRANSPORTATION SYSTEM (ITS), VANET, V2I, V2V.
Concept based Attention
Venue: arXiv cs.AI 2016
Year: 2016

Attention endows animals an ability to concentrate on the most relevant information among a deluge of distractors at any given time, either through volitionally 'top-down' biasing, or driven by automatically 'bottom-up' saliency of stimuli, in favour of advantageous competition in neural modulations for information processing. Nevertheless, instead of being limited to perceive simple features, human and other advanced animals adaptively learn the world into categories and abstract concepts from experiences, imparting the world meanings. This thesis suggests that the high-level cognitive ability of human is more likely driven by attention basing on abstract perceptions, which is defined as concept based attention (CbA).
Responsibility and Tangible Security: Towards a Theory of User Acceptance of Security Tokens
Venue: arXiv cs.HC 2016
Year: 2016

Security and usability issues with passwords suggest a need for a new authentication scheme. Several alternatives involve a physical device or token. We investigate one such alternative, Pico: an authentication scheme that utilizes multiple wearable devices. We present the grounded theory results of a series of semi-structured interviews for exploring perceptions of this scheme. We found that the idea of carrying physical devices increases perceived personal responsibility for secure authentication, making the risks and inconvenience associated with loss and theft salient for participants. Although our work is focused on Pico, the results of the study contribute to a broader understanding of user perception and concerns of responsibility for any token-based authentication schemes.
Real-time 3D Tracking of Articulated Tools for Robotic Surgery
Venue: arXiv cs.CV 2016
Year: 2016

In robotic surgery, tool tracking is important for providing safe tool-tissue interaction and facilitating surgical skills assessment. Despite recent advances in tool tracking, existing approaches are faced with major difficulties in real-time tracking of articulated tools. Most algorithms are tailored for offline processing with pre-recorded videos. In this paper, we propose a real-time 3D tracking method for articulated tools in robotic surgery. The proposed method is based on the CAD model of the tools as well as robot kinematics to generate online part-based templates for efficient 2D matching and 3D pose estimation. A robust verification approach is incorporated to reject outliers in 2D detections, which is then followed by fusing inliers with robot kinematic readings for 3D pose estimation of the tool. The proposed method has been validated with phantom data, as well as ex vivo and in vivo experiments. The results derived clearly demonstrate the performance advantage of the proposed method when compared to the state-of-the-art.
The Normalization of Co-authorship Networks in the Bibliometric Evaluation: The Government Stimulation Programs of China and Korea
Venue: arXiv cs.DL 2016
Year: 2016

Using co-authored publications between China and Korea in Web of Science (WoS) during the one-year period of 2014, we evaluate the government stimulation program for collaboration between China and Korea. In particular, we apply dual approaches, full integer vs. fractional counting, to collaborative publications in order to better examine both the patterns and contents of Sino-Korean collaboration networks in terms of individual countries and institutions. We first conduct a semi-automatic network analysis of Sino-Korean publications based on the full-integer counting method, and then compare our categorization with contextual rankings using the fractional technique; routines for fractional counting of WoS data are made available at http://www.leydesdorff.net/software/fraction . Increasing international collaboration leads paradoxically to lower numbers of publications and citations using fractional counting for performance measurement. However, integer counting is not an appropriate measure for the evaluation of the stimulation of collaborations. Both integer and fractional analytics can be used to identify important countries and institutions, but with other research questions.
Holding all the ASes: Identifying and Circumventing the Pitfalls of AS-aware Tor Client Design
Venue: arXiv cs.CR 2016
Year: 2016

Traffic correlation attacks to de-anonymize Tor users are possible when an adversary is in a position to observe traffic entering and exiting the Tor network. Recent work has brought attention to the threat of these attacks by network-level adversaries (e.g., Autonomous Systems). We perform a historical analysis to understand how the threat from AS-level traffic correlation attacks has evolved over the past five years. We find that despite a large number of new relays added to the Tor network, the threat has grown. This points to the importance of increasing AS-level diversity in addition to capacity of the Tor network. We identify and elaborate on common pitfalls of AS-aware Tor client design and construction. We find that succumbing to these pitfalls can negatively impact three major aspects of an AS-aware Tor client -- (1) security against AS-level adversaries, (2) security against relay-level adversaries, and (3) performance. Finally, we propose and evaluate a Tor client -- Cipollino -- which avoids these pitfalls using state-of-the-art in network-measurement. Our evaluation shows that Cipollino is able to achieve better security against network-level adversaries while maintaining security against relay-level adversaries and
Robust and Efficient Relative Pose with a Multi-camera System for Autonomous Vehicle in Highly Dynamic Environments
Venue: arXiv cs.RO 2016
Year: 2016

This paper studies the relative pose problem for autonomous vehicle driving in highly dynamic and possibly cluttered environments. This is a challenging scenario due to the existence of multiple, large, and independently moving objects in the environment, which often leads to excessive portion of outliers and results in erroneous motion estimation. Existing algorithms cannot cope with such situations well. This paper proposes a new algorithm for relative pose using a multi-camera system with multiple non-overlapping individual cameras. The method works robustly even when the numbers of outliers are overwhelming. By exploiting specific prior knowledge of driving scene we have developed an efficient 4-point algorithm for multi-camera relative pose, which admits analytic solutions by solving a polynomial root-finding equation, and runs extremely fast (at about 0.5$u$s per root). When the solver is used in combination with RANSAC, we are able to quickly prune unpromising hypotheses, significantly improve the chance of finding inliers. Experiments on synthetic data have validated the performance of the proposed algorithm. Tests on real data further confirm the method's practical relevance.
Constant Envelope Signaling in MIMO Channels
Venue: arXiv cs.IT 2016
Year: 2016

The capacity of the point-to-point vector Gaussian channel under the peak power constraint is not known in general. This paper considers a simpler scenario in which the input signal vector is forced to have a constant envelope (or norm). The capacity-achieving distribution for the non-identity $2\times 2$ MIMO channel when the input vector lies on a circle in $\mathbb{R}^2$ is obtained and is shown to have a finite number of mass points on the circle. Subsequently, it is shown that the degrees of freedom (DoF) of a full-rank $n$ by $n$ channel with constant envelope signaling is $n-1$ and it can be achieved by a uniform distribution over the surface of the hypersphere whose radius is defined by the constant envelope. Finally, for the 2 by 2 channel, the power allocation scheme of the constant envelope signaling is compared with that of the conventional case, in which the constraint is on the average transmitted power. It is observed that when the condition number of the channel is close to one, both schemes have a similar trend while this is not the case as the condition number grows.
Optimizing human-interpretable dialog management policy using Genetic Algorithm
Venue: arXiv cs.HC 2016
Year: 2016

Automatic optimization of spoken dialog management policies that are robust to environmental noise has long been the goal for both academia and industry. Approaches based on reinforcement learning have been proved to be effective. However, the numerical representation of dialog policy is human-incomprehensible and difficult for dialog system designers to verify or modify, which limits its practical application. In this paper we propose a novel framework for optimizing dialog policies specified in domain language using genetic algorithm. The human-interpretable representation of policy makes the method suitable for practical employment. We present learning algorithms using user simulation and real human-machine dialogs respectively.Empirical experimental results are given to show the effectiveness of the proposed approach.
On the Convergent Properties of Word Embedding Methods
Venue: arXiv cs.CL 2016
Year: 2016

Do word embeddings converge to learn similar things over different initializations? How repeatable are experiments with word embeddings? Are all word embedding techniques equally reliable? In this paper we propose evaluating methods for learning word representations by their consistency across initializations. We propose a measure to quantify the similarity of the learned word representations under this setting (where they are subject to different random initializations). Our preliminary results illustrate that our metric not only measures a intrinsic property of word embedding methods but also correlates well with other evaluation metrics on downstream tasks. We believe our methods are is useful in characterizing robustness -- an important property to consider when developing new word embedding methods.
FlowIntent: Detecting Privacy Leakage from User Intention to Network Traffic Mapping
Venue: arXiv cs.CR 2016
Year: 2016

The exponential growth of mobile devices has raised concerns about sensitive data leakage. In this paper, we make the first attempt to identify suspicious location-related HTTP transmission flows from the user's perspective, by answering the question: Is the transmission user-intended? In contrast to previous network-level detection schemes that mainly rely on a given set of suspicious hostnames, our approach can better adapt to the fast growth of app market and the constantly evolving leakage patterns. On the other hand, compared to existing system-level detection schemes built upon program taint analysis, where all sensitive transmissions as treated as illegal, our approach better meets the user needs and is easier to deploy. In particular, our proof-of-concept implementation (FlowIntent) captures sensitive transmissions missed by TaintDroid, the state-of-the-art dynamic taint analysis system on Android platforms. Evaluation using 1002 location sharing instances collected from more than 20,000 apps shows that our approach achieves about 91% accuracy in detecting illegitimate location transmissions.
Network Traffic Obfuscation and Automated Internet Censorship
Venue: arXiv cs.NI 2016
Year: 2016

Internet censors seek ways to identify and block internet access to information they deem objectionable. Increasingly, censors deploy advanced networking tools such as deep-packet inspection (DPI) to identify such connections. In response, activists and academic researchers have developed and deployed network traffic obfuscation mechanisms. These apply specialized cryptographic tools to attempt to hide from DPI the true nature and content of connections. In this survey, we give an overview of network traffic obfuscation and its role in circumventing Internet censorship. We provide historical and technical background that motivates the need for obfuscation tools, and give an overview of approaches to obfuscation used by state of the art tools. We discuss the latest research on how censors might detect these efforts. We also describe the current challenges to censorship circumvention research and identify concrete ways for the community to address these challenges.
Causal Discovery for Manufacturing Domains
Venue: arXiv cs.LG 2016
Year: 2016

Yield and quality improvement is of paramount importance to any manufacturing company. One of the ways of improving yield is through discovery of the root causal factors affecting yield. We propose the use of data-driven interpretable causal models to identify key factors affecting yield. We focus on factors that are measured in different stages of production and testing in the manufacturing cycle of a product. We apply causal structure learning techniques on real data collected from this line. Specifically, the goal of this work is to learn interpretable causal models from observational data produced by manufacturing lines. Emphasis has been given to the interpretability of the models to make them actionable in the field of manufacturing. We highlight the challenges presented by assembly line data and propose ways to alleviate them.We also identify unique characteristics of data originating from assembly lines and how to leverage them in order to improve causal discovery. Standard evaluation techniques for causal structure learning shows that the learned causal models seem to closely represent the underlying latent causal relationship between different factors in the production process. These results were also validated by manufacturing domain experts who found them promising. This work demonstrates how data mining and knowledge discovery can be used for root cause analysis in the domain of manufacturing and connected industry.